Tabla de Contenidos: “…Chapter 1: Introduction to Spark 3.1 -- Chapter 2: Manage Data with PySpark -- Chapter 3: Introduction to Machine Learning -- Chapter 4: Linear Regression with PySpark -- Chapter 5: Logistic Regression with PySpark -- Chapter 6: Ensembling with PySpark -- Chapter 7: Clustering with PySpark -- Chapter 8: Recommendation Engine with PySpark -- Chapter 9: Advanced Feature Engineering with PySpark…”

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“…He presents realistic use cases and up-to-date example code for: Spark, the next generation in-memory computing technology from UC Berkeley Storm, the parallel real-time Big Data analytics technology from Twitter GraphLab, the next-generation graph processing paradigm from CMU and the University of Washington (with comparisons to alternatives such as Pregel and Piccolo) Halo also offers architectural and design guidance and code sketches for scaling machine learning algorithms to Big Data, and then realizing them in real-time. …”

Tabla de Contenidos: “…Chapter 1 - Scala Language -- Chapter 2 - Installing Scala -- Chapter 3 - Using Scala Shell -- Chapter 4 – Variables -- Chapter 5 - Data Types -- Chapter 6 - Conditional Statements -- Chapter 7 - Code Blocks -- Chapter 8 – Functions -- Chapter 9 - Scala collections -- Chapter 10 – Loops -- Chapter 11 - Using classes and packages -- Chapter 12 - Exception Handling -- Chapter 13 -- Chapter 14 - Hello World in Apache Spark…”

Tabla de Contenidos: “…Optimizing Databricks Workloads: Harness the power of Apache Spark in Azure and maximize the performance of modern big data workloads…”

Tabla de Contenidos: “…Intro -- Title Page -- Copyright and Credits -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1 - Working with Apache Spark and Delta Lake -- Chapter 1: Data Ingestion and Data Extraction with Apache Spark -- Technical requirements -- Reading CSV data with Apache Spark -- How to do it... -- There's more... -- See also -- Reading JSON data with Apache Spark -- How to do it... -- There's more... -- See also -- Reading Parquet data with Apache Spark -- How to do it... -- See also -- Parsing XML data with Apache Spark -- How to do it... -- There's more... -- See also -- Working with nested data structures in Apache Spark -- How to do it... -- There's more... -- See also -- Processing text data in Apache Spark -- How to do it... -- There's more... -- See also -- Writing data with Apache Spark -- How to do it... -- There's more... -- See also -- Chapter 2: Data Transformation and Data Manipulation with Apache Spark -- Technical requirements -- Applying basic transformations to data with Apache Spark -- How to do it... -- There's more... -- See also -- Filtering data with Apache Spark -- How to do it... -- There's more... -- See also -- Performing joins with Apache Spark -- How to do it... -- There's more... -- See also -- Performing aggregations with Apache Spark -- How to do it... -- There's more... -- See also -- Using window functions with Apache Spark -- How to do it... -- There's more... -- Writing custom UDFs in Apache Spark -- How to do it... -- There's more... -- See also -- Handling null values with Apache Spark -- How to do it... -- There's more... -- See also -- Chapter 3: Data Management with Delta Lake -- Technical requirements -- Creating a Delta Lake table -- How to do it... -- There's more... -- See also -- Reading a Delta Lake table -- How to do it... -- There's more... -- See also -- Updating data in a Delta Lake table -- How to do it…”